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Objectives <p>Deep learning reconstruction (DLR) has shown promising image denoising ability, but its radiation dose reduction potential remains unknown. The objective of this study was to investigate the diagnostic performance of DLR compared to iterative reconstruction (IR) in the detection of liver lesions at standard-dose and reduced-dose CT.</p> Materials and methods <p>Participants with known liver metastases from gastrointestinal and pancreatic adenocarcinoma were prospectively included from routine follow-up (October 2020 to March 2022). Participants received standard-dose CT and two additional reduced-dose scans during the same contrast administration, each reconstructed with IR and high-strength DLR. Two radiologists evaluated images for the presence of liver lesions, and a third established a reference standard. Diagnostic performance was compared using McNemar’s test and mixed effects logistic regression.</p> Results <p>Forty-four participants (mean age 66 years ± 11 [standard deviation], 28 men) were evaluated with 348 included liver lesions ≤ 20 mm (297 metastases, 51 benign; mean size 9.1 ± 4.3 mm). Mean volume CT dose index was 14.2, 7.8 mGy, and 5.1 mGy. Between algorithms, no significant difference in lesion detection was observed within dose levels. Detection of 233 lesions ≤ 10 mm was deteriorated with lower dose levels despite DLR denoising, with 185 detected at standard-dose IR (79.4%; 95% CI: 73.5–84.3) vs 128 at medium-dose DLR (54.9%; 95% CI: 48.3–61.4; <i>p</i> &lt; 0.001) and 105 at low-dose DLR (45.1%; 95% CI: 38.6–51.7; <i>p</i> &lt; 0.001).</p> Conclusion <p>Diagnostic performance for liver lesion detection was comparable between algorithms. When the detection of smaller lesions is important, DLR did not facilitate substantial dose reduction.</p> Key Points <p><Emphasis Type="BoldItalic">Question</Emphasis> <i>Methods to reduce CT radiation dose are desirable in clinical practice, and DLR has shown promising image denoising capabilities</i>.</p> <p><Emphasis Type="BoldItalic">Findings</Emphasis> <i>Liver lesion detection was comparable for DLR and IR across dose levels, but detection of smaller lesions deteriorated with lower dose levels</i>.</p> <p><Emphasis Type="BoldItalic">Clinical relevance</Emphasis> <i>Although potent in image noise reduction, the diagnostic performance of DLR is comparable to IR at standard-dose and reduced-dose CT. Care must be taken in pursuit of dose reduction when the detection and characterization of smaller liver lesions are of clinical importance</i>.</p> Graphical Abstract <p></p>

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Deep learning reconstruction for detection of liver lesions at standard-dose and reduced-dose abdominal CT

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月19日

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  • Tormund H. Njølstad,
  • Kristin Jensen,
  • Hilde K. Andersen,
  • Audun E. Berstad,
  • Gaute Hagen,
  • Cathrine K. Johansen,
  • Kjetil Øye,
  • Jan Glittum,
  • Anniken Dybwad,
  • Emma Thingstad,
  • Marianne G. Guren,
  • Johann Baptist Dormagen,
  • Anselm Schulz

摘要

Objectives

Deep learning reconstruction (DLR) has shown promising image denoising ability, but its radiation dose reduction potential remains unknown. The objective of this study was to investigate the diagnostic performance of DLR compared to iterative reconstruction (IR) in the detection of liver lesions at standard-dose and reduced-dose CT.

Materials and methods

Participants with known liver metastases from gastrointestinal and pancreatic adenocarcinoma were prospectively included from routine follow-up (October 2020 to March 2022). Participants received standard-dose CT and two additional reduced-dose scans during the same contrast administration, each reconstructed with IR and high-strength DLR. Two radiologists evaluated images for the presence of liver lesions, and a third established a reference standard. Diagnostic performance was compared using McNemar’s test and mixed effects logistic regression.

Results

Forty-four participants (mean age 66 years ± 11 [standard deviation], 28 men) were evaluated with 348 included liver lesions ≤ 20 mm (297 metastases, 51 benign; mean size 9.1 ± 4.3 mm). Mean volume CT dose index was 14.2, 7.8 mGy, and 5.1 mGy. Between algorithms, no significant difference in lesion detection was observed within dose levels. Detection of 233 lesions ≤ 10 mm was deteriorated with lower dose levels despite DLR denoising, with 185 detected at standard-dose IR (79.4%; 95% CI: 73.5–84.3) vs 128 at medium-dose DLR (54.9%; 95% CI: 48.3–61.4; p < 0.001) and 105 at low-dose DLR (45.1%; 95% CI: 38.6–51.7; p < 0.001).

Conclusion

Diagnostic performance for liver lesion detection was comparable between algorithms. When the detection of smaller lesions is important, DLR did not facilitate substantial dose reduction.

Key Points

Question Methods to reduce CT radiation dose are desirable in clinical practice, and DLR has shown promising image denoising capabilities.

Findings Liver lesion detection was comparable for DLR and IR across dose levels, but detection of smaller lesions deteriorated with lower dose levels.

Clinical relevance Although potent in image noise reduction, the diagnostic performance of DLR is comparable to IR at standard-dose and reduced-dose CT. Care must be taken in pursuit of dose reduction when the detection and characterization of smaller liver lesions are of clinical importance.

Graphical Abstract